Estimating an endpoint with high order moments

Stephane Girard 1 Armelle Guillou 2 Gilles Stupfler 2
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We present a new method for estimating the endpoint of a unidimensional sample when the distribution function decreases at a polynomial rate to zero in the neighborhood of the endpoint. The estimator is based on the use of high order moments of the variable of interest. It is assumed that the order of the moments goes to infinity, and we give conditions on its rate of divergence to get the asymptotic normality of the estimator. The good performance of the estimator is illustrated on some finite sample situations.
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Stephane Girard, Armelle Guillou, Gilles Stupfler. Estimating an endpoint with high order moments. Test, Spanish Society of Statistics and Operations Research/Springer, 2012, 21 (4), pp.697-729. ⟨10.1007/s11749-011-0277-8⟩. ⟨inria-00596979⟩

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